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《天津医科大学学报》[ISSN:1006-8147/CN:12-1259/R]

卷:

25卷

期数:

2019年01期

页码:

32-36

栏目:

基础医学

出版日期:

2019-01-20

文章信息/Info

Title:

Bioinformatics analysis of key genes for tamoxifen resistancein estrogen receptor positive breast cancer

文章编号:

1006-8147(2019)01-0032-05

作者:

王世霞; 杨艳芳; 马 宁; 刘 君

（天津医科大学肿瘤医院乳腺肿瘤二科，国家肿瘤临床医学研究中心，乳腺癌防治教育部重点实验室，天津市“肿瘤防治”重点实验室，天津市恶性肿瘤临床医学研究中心，天津 300060）

Author(s):

WANG Shi-xia;  YANG Yan-fang;  MA Ning;  LIU Jun

（Department of The Second Breast Cancer, Cancer Institute and Hospital, Tianjin Medical University, National Clinical Research Center of Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin’s clinical Research Center for Cancer, Tianjin 300060, China)

关键词:

乳腺癌; 他莫昔芬耐药; 差异表达基因; 生物信息学

Keywords:

breast cancer;  tamoxifen resistance;  differentially expressed genes;  bioinformatics

分类号:

R737.9

DOI:

-

文献标志码:

A

摘要:

目的：从分子水平揭示激素受体阳性乳腺癌他莫昔芬耐药的机制，并寻找潜在的治疗他莫昔芬耐药的靶点。方法：从公共基因芯片表达数据库（GEO）中下载雌激素受体阳性乳腺癌的相关基因芯片数据GSE67916，利用GEO2R在线分析工具筛选他莫昔芬耐药性与敏感性乳腺癌的差异表达基因；并利用DAVID软件对所筛选差异表达基因进行相关功能及通路富集分析；通过STRING、Cytoscape等工具对其进行蛋白间相互作用网络的构建和分析。结果:筛选出438个差异表达基因，其中300个上调表达基因，138个下调表达基因。GO功能分析发现这些差异基因主要参与蛋白结合、细胞对雌激素的反应、免疫应答、细胞质及细胞外基质等分子功能及生物学过程；KEGG通路富集分析显示主要富集在MAPK信号通路和HIF-1信号通路等。STRING、Cytoscape分析显示MAPK1、ESR1、SMARCA4、RANBP2和PRKCA为潜在的关键节点基因，对其进行文献挖掘及分析显示与激素受体阳性乳腺癌他莫昔芬耐药相关。结论:利用生物信息学方法对他莫昔芬耐药与他莫昔芬敏感的雌激素受体阳性乳腺癌的差异表达基因分析，可有效发掘这些差异表达基因的相互作用，为雌激素受体阳性乳腺癌他莫昔芬耐药寻找新的治疗靶点提供新方向。

Abstract:

Objective: To investigate the molecular mechanisms in resistance of tamoxifen in ER positive breast cancer and identify potential targets for anti-tamoxifen resistance. Methods: The GSE67916 gene data aboutestrogen receptor-positive breast cancer were downloaded from the Gene Expression Omnibus database. GEO2R online tool was used to mine and screen the differentially expressed genes (DEGs) between tamoxifen-resistant and tamoxifen-sensitive breast cancer. Gene Ontology (GO) and pathway enrichment analyses were applied to investigate the functions and pathways of these DEGs by using DAVID. Subsequently, the protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized using the Cytoscape software. Results: In total, we found 438 DEGs, of which 300 genes were up-regulated and 138 genes were down-regulated. By using the GO and KEGG analysis, the DEGs were significantly enhanced in the protein binding, cellular response to estradiol stimulus, immune response, cytoplasm and extracellular exosome and so on, while the most significant pathways included MAPK signaling pathway，HIF-1 signaling pathwayand so on. The key node genes of MAPK1, ESR1, SMARCA4, RANBP2 and PRKCA were found in the PPI network via STRING and Cytoscape. Finally, It was discovered that these genes may be related to tamoxifen resistance in hormone receptor positive breast cancer.Conclusion: By bioinformatics methods to analyze DEGs in tamoxifen-resistantand tamoxifen-sensitive estrogen receptor positive breast cancer, we have discovered the interaction information of these differentially expressed genes and it could make a contribution to the development of therapeutic targets for tamoxifen resistance in estrogenreceptor positive breast cancer.

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备注/Memo

备注/Memo:

作者简介 王世霞（1991-），女，硕士在读，研究方向：肿瘤学；通信作者：刘君，E-mail：dr_liujun@126.com。

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更新日期/Last Update: 2019-03-01